Mixture of latent trait analyzers for model-based clustering of categorical data

Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspondence between the estimated latent classes and groups in the population of interest. The mixture of latent trait analyzers model extends latent class analysis by assuming a model for the categorical response variables that depends on both a categorical latent class and a continuous latent trait variable; the discrete latent class accommodates group structure and the continuous latent trait accommodates dependence within these groups. Fitting the mixture of latent trait analyzers model is potentially difficult because the likelihood function involves an integral that cannot be evaluated analytically. We develop a variational approach for fitting the mixture of latent trait models and this provides an efficient model fitting strategy. The mixture of latent trait analyzers model is demonstrated on the analysis of data from the National Long Term Care Survey (NLTCS) and voting in the U.S. Congress. The model is shown to yield intuitive clustering results and it gives a much better fit than either latent class analysis or latent trait analysis alone

Evaluation of Chemical Constituents and Antioxidant Activity of Coconut Water (Cocus nucifera L.) and Caffeic Acid in Cell Culture

Coconut water contains several uncharacterized substances and is widely used in the human consumption. In this paper we detected and quantified ascorbic acid and caffeic acid and total phenolics in several varieties of coconut using HPLS/MS/MS (25.8 ± 0.6 µg/mL and 1.078 ± 0.013 µg/mL and 99.7 µg/mL, respectively, in the green dwarf coconut water, or 10 mg and 539 µg and 39.8 mg for units of coconut consumed, 500 ± 50 mL). The antioxidant potential of four coconut varieties (green dwarf, yellow dwarf, red dwarf and yellow Malaysian) was compared with two industrialized coconut waters and the lyophilized water of the green dwarf variety. All varieties were effective in scavenging the DPPH radical (IC50=73 µL) and oxide nitric (0.1 mL with an IP of 29.9%) as well as in inhibiting the in vitro production of thiobarbituric acid reactive substances (1 mL with an IP of 34.4%), highlighting the antioxidant properties of the green dwarf which it is the most common used. In cell culture, the green dwarf water was efficient in protecting against oxidative damages induced by hydrogen peroxide